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https://github.com/ml-explore/mlx.git
synced 2025-08-28 00:36:32 +08:00
Remove stream from average grads so it uses default
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30561229c7
commit
d08fa4bef8
@ -76,7 +76,6 @@ def average_gradients(
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group: Optional[mx.distributed.Group] = None,
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all_reduce_size: int = 32 * 1024**2,
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communication_type: Optional[mx.Dtype] = None,
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stream: mx.Stream = mx.cpu,
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):
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"""Average the gradients across the distributed processes in the passed group.
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@ -95,7 +94,6 @@ def average_gradients(
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communication_type (Optional[mlx.core.Dtype]): If provided cast to this
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type before performing the communication. Typically cast to a
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smaller float to reduce the communication size. Default: ``None``.
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stream (mlx.core.Stream): The stream to use for the reduction. Default: ``mlx.cpu``.
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"""
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group = group or mx.distributed.init()
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N = group.size()
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@ -106,7 +104,7 @@ def average_gradients(
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def _average(x):
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dt = x.dtype
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x = x.astype(communication_type) if communication_type is not None else x
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return mx.distributed.all_sum(x, stream=stream).astype(dt) / N
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return mx.distributed.all_sum(x).astype(dt) / N
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if all_reduce_size <= 0:
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return tree_map(_average, gradients)
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@ -65,21 +65,21 @@ class TestNCCLDistributed(mlx_tests.MLXTestCase):
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mx.distributed.all_sum = new_all_sum
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try:
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grads = [mx.ones(10) for i in range(10)]
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new_grads = average_gradients(grads, stream=mx.gpu)
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new_grads = average_gradients(grads)
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mx.eval(new_grads)
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self.assertEqual(len(new_grads), 10)
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self.assertTrue(all(mx.all(g == 1) for g in new_grads))
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self.assertEqual(n_calls, 1)
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n_calls = 0
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new_grads = average_gradients(grads, all_reduce_size=4 * 50, stream=mx.gpu)
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new_grads = average_gradients(grads, all_reduce_size=4 * 50)
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mx.eval(new_grads)
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self.assertEqual(len(new_grads), 10)
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self.assertTrue(all(mx.all(g == 1) for g in new_grads))
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self.assertEqual(n_calls, 2)
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n_calls = 0
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new_grads = average_gradients(grads, all_reduce_size=0, stream=mx.gpu)
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new_grads = average_gradients(grads, all_reduce_size=0)
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mx.eval(new_grads)
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self.assertEqual(len(new_grads), 10)
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self.assertTrue(all(mx.all(g == 1) for g in new_grads))
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@ -91,7 +91,6 @@ class TestNCCLDistributed(mlx_tests.MLXTestCase):
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grads,
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all_reduce_size=2 * 50,
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communication_type=mx.float16,
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stream=mx.gpu,
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)
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mx.eval(new_grads)
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self.assertEqual(len(new_grads), 10)
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